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    Closed-Form Fragility Estimates, Parameter Sensitivity, and Bayesian Updating for RC Columns

    Source: Journal of Engineering Mechanics:;2007:;Volume ( 133 ):;issue: 007
    Author:
    Do-Eun Choe
    ,
    Paolo Gardoni
    ,
    David Rosowsky
    DOI: 10.1061/(ASCE)0733-9399(2007)133:7(833)
    Publisher: American Society of Civil Engineers
    Abstract: Reinforced concrete (RC) columns are the most critical components in bridges under seismic excitation. In this paper, a simple closed-form formulation to estimate the fragility of RC columns is developed. The formulation is used to estimate the conditional probability of failure of an example column for given shear and deformation demands. The estimated fragilities are as accurate as more sophisticated estimates (i.e., predictive fragilities) and do not require any reliability software. A sensitivity analysis is carried out to identify to which parameter(s) the reliability of the example column is most sensitive. The closed-form formulation uses probabilistic capacity models. A Bayesian procedure is presented to update existing probabilistic models with new data. The model updating process can incorporate different types of information, including laboratory test data, field observations, and subjective engineering judgment, as they become available.
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      Closed-Form Fragility Estimates, Parameter Sensitivity, and Bayesian Updating for RC Columns

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    contributor authorDo-Eun Choe
    contributor authorPaolo Gardoni
    contributor authorDavid Rosowsky
    date accessioned2017-05-08T22:41:14Z
    date available2017-05-08T22:41:14Z
    date copyrightJuly 2007
    date issued2007
    identifier other%28asce%290733-9399%282007%29133%3A7%28833%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/86451
    description abstractReinforced concrete (RC) columns are the most critical components in bridges under seismic excitation. In this paper, a simple closed-form formulation to estimate the fragility of RC columns is developed. The formulation is used to estimate the conditional probability of failure of an example column for given shear and deformation demands. The estimated fragilities are as accurate as more sophisticated estimates (i.e., predictive fragilities) and do not require any reliability software. A sensitivity analysis is carried out to identify to which parameter(s) the reliability of the example column is most sensitive. The closed-form formulation uses probabilistic capacity models. A Bayesian procedure is presented to update existing probabilistic models with new data. The model updating process can incorporate different types of information, including laboratory test data, field observations, and subjective engineering judgment, as they become available.
    publisherAmerican Society of Civil Engineers
    titleClosed-Form Fragility Estimates, Parameter Sensitivity, and Bayesian Updating for RC Columns
    typeJournal Paper
    journal volume133
    journal issue7
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)0733-9399(2007)133:7(833)
    treeJournal of Engineering Mechanics:;2007:;Volume ( 133 ):;issue: 007
    contenttypeFulltext
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